The final goal of the present project is to develop a ship detection and identification system by integrating spaceborne synthetic aperture radar (SAR), ground-based maritime radar and automatic identification system (AIS); and this article presents the results of the first phase experiments and current status toward achieving this goal. The data acquired by the Phased Array L-band SAR (PALSAR) on board of the Advanced Land Observing Satellite (ALOS) were used as SAR data, and X-band maritime radar including AIS were used as a ground-based system. The work is divided into two experimental phases. The first phase is to examine the ability of PALSAR to detect ships whose sizes are comparable with the SAR resolution cells, and the second is to incorporate the PALSAR data with those acquired by the ground-based radar with AIS. For the experiments in the first phase, we deployed three small fishing boats whose lengths ranged from approximately 8 m to 15 m in the Tosa Bay in Kochi, Japan in 2006. The experiments were carried out for four observation PALSAR modes: FBS (Fine Beam Single) 34.3, FBS 21.5, FBD (Fine Beam Double) 41.5, and PLR (PoLaRimetric) 20.5, where the numbers in each modes represent the off-nadir angles. For extracting the boats from the PALSAR images, five algorithms were considered, including amplitude-based, CFAR (Constant False Alarm Rate), MLCC (Multi-Look Cross-Correlation), CCF (Cross-Correlation Function) of HH- and HV-polarization amplitudes, and polarimetric analyses. This paper summarizes the results of the first phase experiments; the summary of the integrated system in the second phase will be reported in the near future.

The GMM-UBM framework has been proved to be one of the most effective approaches to the automatic speaker verification (ASV) task in recent years. In this letter, we first propose an approximate decision function of traditional GMM-UBM, from which it is shown that the contribution to classification of each Gaussian component is equally important. However, research in speaker perception shows that a different speech sound unit defined by Gaussian component makes a different contribution to speaker verification. This motivates us to emphasize some sound units which have discriminability between speakers while de-emphasize the speech sound units which contain little information for speaker verification. Experiments on 2006 NIST SRE core task show that the proposed approach outperforms traditional GMM-UBM approach in classification accuracy.

In this paper, the Getis statistic is applied to ALOS- PALSAR (Advanced Land Ovserving Satellite-Phased Array L-band Synthetic Aperture Radar) images for assessing the building damage caused by the Wenchuan earthquake in 2008. As a proposed image analysis, a simulated building image using mapping and projection algorithm is first presented for analysis of the Getis statistic. The results show the high accuracy of the assessment of the proposed approach. The Getis statistic is then applied to two ALOS-PALSAR images acquired before and after the Wenchuan earthquake to assess the level of building damage. Results of the Getis statistic show that the damage level is approximately 81%.

This article presents the analysis of the Bragg scattering phenomenon which has been observed in the images of machine-planted rice paddies acquired by the JERS-1 L-band synthetic aperture radar (SAR). The simultaneous measurements of rice plants were made at the SAR data acquisition times. Large differences of 20-25 dB in image intensity between the transplanting and ripening stages are found to be dependent on the planting direction and bunch separation. This selective image enhancement is a result of the Bragg resonance backscatter due to the double-bounce of incident L-band microwave between the flooded water surface and periodically planted bunches of rice plants. Support for the idea of double-bounce scattering is provided by the decomposition analysis of L-band and X-band polarimetric Pi-SAR data; and a simple numerical simulation based on the physical optics model shows fairly good agreement with the JERS-1 SAR data. The results presented in this paper is mainly of academic interest, but a suggestion can be made on the selection of suitable microwave band for monitoring rice fields.

An inversion method of bridge height over water by polarimetric synthetic aperture radar (SAR) is developed. A geometric ray description to illustrate scattering mechanism of a bridge over water surface is identified by polarimetric image analysis. Using the mapping and projecting algorithm, a polarimetric SAR image of a bridge model is first simulated and shows that scattering from a bridge over water can be identified by three strip lines corresponding to single-, double-, and triple-order scattering, respectively. A set of polarimetric parameters based on the de-orientation theory is applied to analysis of three types scattering, and the thinning-clustering algorithm and Hough transform are then employed to locate the image positions of these strip lines. These lines are used to invert the bridge height. Fully polarimetric image data of airborne Pi-SAR at X-band are applied to inversion of the height and width of the Naruto Bridge in Japan. Based on the same principle, this approach is also applicable to spaceborne ALOSPALSAR single-polarization data of the Eastern Ocean Bridge in China. The results show good feasibility to realize the bridge height inversion.